In this project we have created a music database which can be a part of a much larger application of online music streaming. The database keeps record of all the songs and its properties as well as all the artists and their details. Moreover, it also keeps track of the all the users, their playlists and the songs in their playlists.
The idea is to capture the user’s taste of music by storing the details of the songs like song name, song genre, artist, number of times user listened to a song etc. so that the analysts can use this data to design a recommender system and to improve the song base. The amount of data that can be collected for creating a music library is quite large. For the purpose of this project, we used two Kaggle datasets of Spotify top tracks and artists to create the database. We also generated synthetic data for user details, playlists etc. Database management system is necessary for this application since it consumes a huge amount of space, and many users access it at the same time from various locations. The database is administered by admins, who can add/delete songs as well as users from their region. Thus, there are two login pages, one for users and other for admins with different functions associated with these accounts. Some of the admin functions include, inserting new songs, deleting old songs, deleting and monitoring users. Moreover, some of the user functions are, viewing or searching songs/artists, creating playlists, deleting playlists, etc.